Johann Glaser

Fmri Artifact Correction in Eeg and Emg Data: Introducing Facet: a Flexible Artifact Correction and Evaluation Toolbox for Eeg / Fmri Data Johann Glaser

The concurrent acquisition of EEG and fMRI allows to combine the high spatial resolution of fMRI and the high temporal resolution of EEG. However, the rapidly changing magnetic fields of the fMRI gradient system lead to artifacts in the EEG signal which are several orders of magnitude above the measured brain activity. To correct these artifacts, a new universal toolbox ?FACET ? a Flexible Artifact Correction and Evaluation Toolbox for EEG/fMRI data? was developed in the course of the author's diploma thesis at the University of Vienna. It provides facilities for the analysis of the EEG/EMG data and fMRI gradient artifacts, for the correction of these artifacts and for the evaluation of the correction results. This unique combination of all three features allows to iteratively optimize the configuration of the algorithm specifically to the data. The toolbox is extensible at any point and provides multiple improvements over existing algorithms. It is available online at https://github.com/hansiglaser/ facet as open source software under the terms of the GNU General Public License.